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commerce_product_graph_query

Query product relationships and attributes in the commerce domain using natural language objectives or structured inputs.

Instructions

Run the commerce domain agent action product_graph_query.

Routes through the platform's domain-agent dispatcher under your JWT, tenant, and company scope.

Args: message: Free-text objective for the action. inputs: Optional JSON string of structured inputs for the action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNo
inputsNo{}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses that it routes through a domain-agent dispatcher under JWT/tenant/company scope, but does not state whether the tool is read-only, has side effects, or any behavioral traits. No annotations exist to supplement this.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, uses clear paragraphs and a bullet list for arguments. It avoids unnecessary elaboration, making it easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema, the description does not mention what the tool returns. It also lacks context about the product graph domain, leaving the agent with insufficient information to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds basic meaning: 'message' is a free-text objective and 'inputs' is an optional JSON string. However, with 0% schema coverage, this is insufficient to clarify expected formats, constraints, or examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Run the commerce domain agent action `product_graph_query`' but does not explain what the action does. The name suggests querying a product graph, but no details are provided to distinguish it from similar commerce tools like commerce_product_analysis or commerce_catalog_sync.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool vs alternatives. The description only mentions routing and authentication scope, but no conditional usage or exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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